Run
51655

Run 51655

Task 1748 (Learning Curve) tic-tac-toe Uploaded 06-11-2014 by Joaquin Vanschoren
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


Flow

weka.MultiBoostAB_RandomTree(2)Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
weka.RandomTree(2)_K0
weka.RandomTree(2)_M1.0
weka.RandomTree(2)_S1
weka.RandomTree(2)_V0.001
weka.MultiBoostAB_RandomTree(2)_C3
weka.MultiBoostAB_RandomTree(2)_P100
weka.MultiBoostAB_RandomTree(2)_S1
weka.MultiBoostAB_RandomTree(2)_I10
weka.MultiBoostAB_RandomTree(2)_Wweka.classifiers.trees.RandomTree

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

model
Model readable

A human-readable description of the model that was built.

model
Model serialized

A serialized description of the model that can be read by the tool that generated it.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

21 Evaluation measures

Area under ROC curve
0.8218 ± 0.0632
Per class
Build CPU time
0.0017
Build memory
865116513.4222
F measure
0.8278 ± 0.0544
Per class
Kappa
0.62 ± 0.1189
KB relative information score
0.6008 ± 0.1171
Mean absolute error
0.174 ± 0.0513
Mean prior absolute error
0.453 ± 0.0013
Number of instances
958
Per class
OS information
[Sun Microsystems Inc., 1.6.0_20, amd64, Linux, 2.6.35.14-106.fc14.x86_64]
Precision
0.8279 ± 0.0563
Per class
Predictive accuracy
0.8278 ± 0.0544
Prior entropy
0.931 ± 0.0039
Recall
0.8278 ± 0.0544
Per class
Relative absolute error
0.384 ± 0.1123
Root mean prior squared error
0.4759 ± 0.0014
Root mean squared error
0.4036 ± 0.0642
Root relative squared error
0.8481 ± 0.1334
SciMark benchmark
948.877